Biodiversity data integration-the significance of data resolution and domain

Disentangling the veil line for Brazilian biodiversity: An overview from two long-term research programs reveals huge gaps in ecological data reporting

The lack of synthesized information regarding biodiversity is a major problem among researchers, leading to a pervasive cycle where ecologists make field campaigns to collect information that already exists and yet has not been made available for a broader audience. This problem leads to long-lasting effects in public policies such as spending money multiple times to conduct similar studies in the same area. We aim to identify this knowledge gap by synthesizing information available regarding two Brazilian long-term biodiversity programs and the metadata generated by them. Using a unique dataset containing 1904 metadata, we identified patterns of metadata distribution and intensity of research conducted in Brazil, as well as where we should concentrate research efforts in the next decades. We found that the majority of metadata were about vertebrates, followed by plants, invertebrates, and fungi. Caatinga was the biome with least metadata, and that there's still a lack of information regarding all biomes in Brazil, with none of them being sufficiently sampled. We hope that these results will have implications for broader conservation and management guiding, as well as to funding allocation programs.

Temporal β-diversity decomposition: Insights into fish biodiversity dynamics in the Moroccan South Atlantic

Understanding the various aspects of temporal β-diversity and their relationships can profoundly enhance the knowledge of the intricate dynamics of biodiversity over temporal scales. In this study, we examined extensive data on fish in the Moroccan South Atlantic, to quantify taxonomic and functional temporal β-diversity over three five-year periods, determine the relative contributions of turnover and nestedness to each facet, and elucidate the relationship between taxonomic and functional temporal β-diversity including their components using temporal and spatial comparisons. Our findings revealed a complex relationship between taxonomic and functional temporal β-diversity, with decoupled variation often observed. Furthermore, the predominant component of functional temporal β-diversity was functional nestedness, while species turnover had a greater impact on taxonomic temporal β-diversity. A noteworthy observation was the significant fluctuation in the turnover and nestedness components, despite consistent temporal β-diversity. These insights underscore the pivotal role of temporal β-diversity decomposition and advocate for the integration of functional aspects in temporal biodiversity research to provide additional key indicators for biodiversity sustainable management.

The ELIXIR Biodiversity Community: Understanding short- and long-term changes in biodiversity

Biodiversity loss is now recognised as one of the major challenges for humankind to address over the next few decades. Unless major actions are taken, the sixth mass extinction will lead to catastrophic effects on the Earth's biosphere and human health and well-being. ELIXIR can help address the technical challenges of biodiversity science, through leveraging its suite of services and expertise to enable data management and analysis activities that enhance our understanding of life on Earth and facilitate biodiversity preservation and restoration. This white paper, prepared by the ELIXIR Biodiversity Community, summarises the current status and responses, and presents a set of plans, both technical and community-oriented, that should both enhance how ELIXIR Services are applied in the biodiversity field and how ELIXIR builds connections across the many other infrastructures active in this area. We discuss the areas of highest priority, how they can be implemented in cooperation with the ELIXIR Platforms, and their connections to existing ELIXIR Communities and international consortia. The article provides a preliminary blueprint for a Biodiversity Community in ELIXIR and is an appeal to identify and involve new stakeholders.

Detecting management gaps for biodiversity conservation: An integrated assessment

The latest report on the state of nature in Europe (2013-2018) shows that biodiversity is declining at an alarming rate, with most protected species and habitats in poor condition. Despite an increasing volume of collected biodiversity information, urgent action is needed to integrate biodiversity data and knowledge to improve conservation efforts. We conducted a study in Catalonia (NE Spain), where we collected management measures implemented between 2013 and 2018, including allocation, budget, pressures aimed, and habitats/species potentially benefiting. We integrated information on pressures and habitats/species with the measures to identify non-spatial management gaps. Then, we integrated the spatially explicit information to determine the spatial management gap, identifying geographical areas where species/habitats are under pressure without registered measures. We demonstrated the importance of integrating existing information. Our findings revealed that resources were often not distributed adequately across species/habitats, with biases towards certain taxa being a common issue. The non-spatial management gap analysis identified taxonomic groups, especially plants and mollusks with the wider management gaps. We also identified threatened areas, especially in the northeast of the region with the larger spatial management gaps. These results could guide priority objectives to optimize conservation efforts. Integrating different information sources provided a broader view of the challenges that conservation science is facing nowadays. Our study offers a path toward bending the curve of biodiversity loss by providing an integrative framework that could optimize the use of the available information and help narrow the knowing-doing gap. In the context of the EU, this example demonstrates how information can be used to promote some environmental policy instruments, such as the Prioritized Action Frameworks (PAFs). Additionally, our findings highlight the importance of supporting decision-making with systematic assessments to identify deficiencies in the conservation process, reduce the loss of critical ecosystems and species, and avoid biases among taxa.

ARAapp: filling gaps in the ecological knowledge of spiders using an automated and dynamic approach to analyze systematically collected community data

The ARAMOB data repository compiles meticulously curated spider community datasets from systematical collections, ensuring a high standard of data quality. These datasets are enriched with crucial methodological data that enable the datasets to be aligned in time and space, facilitating data synthesis across studies, respectively, collections. To streamline the analysis of these datasets in a species-specific context, a suite of tailored ecological analysis tools named ARAapp has been developed. By harnessing the capabilities of ARAapp, users can systematically evaluate the spider species data housed within the ARAMOB repository, elucidating intricate relationships with a range of parameters such as vertical stratification, habitat occurrence, ecological niche parameters (moisture and shading) and phenological patterns. Database URL: ARAapp is available at  www.aramob.de/en.

PhyloSophos: a high-throughput scientific name mapping algorithm augmented with explicit consideration of taxonomic science, and its application on natural product (NP) occurrence database processing

BACKGROUND

The standardization of biological data using unique identifiers is vital for seamless data integration, comprehensive interpretation, and reproducibility of research findings, contributing to advancements in bioinformatics and systems biology. Despite being widely accepted as a universal identifier, scientific names for biological species have inherent limitations, including lack of stability, uniqueness, and convertibility, hindering their effective use as identifiers in databases, particularly in natural product (NP) occurrence databases, posing a substantial obstacle to utilizing this valuable data for large-scale research applications.

RESULT

To address these challenges and facilitate high-throughput analysis of biological data involving scientific names, we developed PhyloSophos, a Python package that considers the properties of scientific names and taxonomic systems to accurately map name inputs to entries within a chosen reference database. We illustrate the importance of assessing multiple taxonomic databases and considering taxonomic syntax-based pre-processing using NP occurrence databases as an example, with the ultimate goal of integrating heterogeneous information into a single, unified dataset.

CONCLUSIONS

We anticipate PhyloSophos to significantly aid in the systematic processing of poorly digitized and curated biological data, such as biodiversity information and ethnopharmacological resources, enabling full-scale bioinformatics analysis using these valuable data resources.

Enhancing biodiversity conservation and monitoring in protected areas through efficient data management

A scientifically informed approach to decision-making is key to ensuring the sustainable management of ecosystems, especially in the light of increasing human pressure on habitats and species. Protected areas, with their long-term institutional mandate for biodiversity conservation, play an important role as data providers, for example, through the long-term monitoring of natural resources. However, poor data management often limits the use and reuse of this wealth of information. In this paper, we share lessons learned in managing long-term data from the Italian Alpine national parks. Our analysis and examples focus on specific issues faced by managers of protected areas, which partially differ from those faced by academic researchers, predominantly owing to different mission, governance, and temporal perspectives. Rigorous data quality control, the use of appropriate data management tools, and acquisition of the necessary skills remain the main obstacles. Common protocols for data collection offer great opportunities for the future, and complete recovery and documentation of time series is an urgent priority. Notably, before data can be shared, protected areas should improve their data management systems, a task that can be achieved only with adequate resources and a long-term vision. We suggest strategies that protected areas, funding agencies, and the scientific community can embrace to address these problems. The added value of our work lies in promoting engagement with managers of protected areas and in reporting and analysing their concrete requirements and problems, thereby contributing to the ongoing discussion on data management and sharing through a bottom-up approach.

Exploring the impact of data curation criteria on the observed geographical distribution of mosses

Biodiversity data records contain inaccuracies and biases. To overcome this limitation and establish robust geographic patterns, ecologists often curate records keeping those that are most suitable for their analyses. Yet, this choice is not straightforward and the outcome of the analysis may vary due to a trade-off between data quality and volume. This problem is particularly recurrent for less-studied groups with patchy sampling effort. The latitudinal pattern of mosses richness remains inconsistent across studies and these may emerge purely from sampling artefacts. Our main objective here is to assess the effect of different curation criteria on this spatial pattern in the Temperate Northern Hemisphere (above 20° latitude). We contrasted the geographical distribution of moss species records and the latitude-species richness relation obtained under different data curation scenarios. These scenarios comprehend five sources of taxonomical standardisations and eight data cleaning filters. The analyses are based on the selection of well-surveyed cells at 100 km cell resolution. The application of some 'data curation scenarios' severely affects the number of records selected for analysis and substantially changes the proportion of richness per cell. The sensitivity to data curation becomes detectable at regional and at the cell scales showing a large shift in the latitudinal richness peak in Europe, from 60° N to 45° N latitude, when only preserved specimens are selected and duplicates based on date of collection and coordinates are excluded. Our results stress the importance of justifying the criteria used for filtering biodiversity data retrieved from biodiversity databases to avoid detecting misleading patterns. Curating records under particular criteria compromises the information in some areas displaying different spatial information of mosses. This problem can be ameliorated if data filtering is combined with identifying well-surveyed cells, render relatively constant results under different combinations of filtering even for less well-known groups such as mosses.

A globally integrated structure of taxonomy to support biodiversity science and conservation

All aspects of biodiversity research, from taxonomy to conservation, rely on data associated with species names. Effective integration of names across multiple fields is paramount and depends on the coordination and organization of taxonomic data. We assess current efforts and find that even key applications for well-studied taxa still lack commonality in taxonomic information required for integration. We identify essential taxonomic elements from our interoperability assessment to support improved access and integration of taxonomic data. A stronger focus on these elements has the potential to involve taxonomic communities in biodiversity science and overcome broken linkages currently limiting research capacity. We encourage a community effort to democratize taxonomic expertise and language in order to facilitate maximum interoperability and integration.

SPARSE 1.0: a template for databases of species inventories, with an open example of Czech birds

Here, we introduce SPARSE (acronym for "SPecies AcRoss ScalEs"), a simple and portable template for databases that can store data on species composition derived from ecological inventories, surveys and checklists, with emphasis on metadata describing sampling effort and methods. SPARSE can accommodate resurveys and time series and data from different spatial scales, as well as complex sampling designs. SPARSE focuses on inventories that report multiple species for a given site, together with sampling methods and effort, which can be used in statistical models of true probability of occurrence of species. SPARSE is spatially explicit and can accommodate nested spatial structures from multiple spatial scales, including sampling designs where multiple sites within a larger area have been surveyed and the larger area can again be nested in an even larger region. Each site in SPARSE is represented either by a point, line (for transects) or polygon, stored in an ESRI shapefile. SPARSE implements a new combination of our own field definitions with Darwin Core biodiversity data standard and its Humboldt core extension. The use of Humboldt core also makes SPARSE suitable for biodiversity data with temporal replication. We provide an example use of the SPARSE framework by digitising data on birds from the Czech Republic, from 348 sites and 524 sampling events, with 15,969 unique species-per-event observations of presence, abundance or population density. To facilitate use without the need for a high-level database expertise, the Czech bird example is implemented as MS Access .accdb file, but can be ported to other database engines. The example of Czech birds complements other bird datasets from the Czech Republic, specifically the four gridded national atlases and the breeding bird survey which cover a similar temporal extent, but different locations and spatial scales.

Phytodiversity is associated with habitat heterogeneity from Eurasia to the Hengduan Mountains

The geographic distribution of plant diversity matches the gradient of habitat heterogeneity from lowlands to mountain regions. However, little is known about how much this relationship is conserved across scales. Using the World Checklist of Vascular Plants and high-resolution biodiversity maps developed by species distribution models, we investigated the associations between species richness and habitat heterogeneity at the scales of Eurasia and the Hengduan Mountains (HDM) in China. Habitat heterogeneity explains seed plant species richness across Eurasia, but the plant species richness of 41/97 HDM families is even higher than expected from fitted statistical relationships. A habitat heterogeneity index combining growing degree days, site water balance, and bedrock type performs better than heterogeneity based on single variables in explaining species richness. In the HDM, the association between heterogeneity and species richness is stronger at larger scales. Our findings suggest that high environmental heterogeneity provides suitable conditions for the diversification of lineages in the HDM. Nevertheless, habitat heterogeneity alone cannot fully explain the distribution of species richness in the HDM, especially in the western HDM, and complementary mechanisms, such as the complex geological history of the region, may have contributed to shaping this exceptional biodiversity hotspot.

Challenges and directions in analytical paleobiology

Over the last 50 years, access to new data and analytical tools has expanded the study of analytical paleobiology, contributing to innovative analyses of biodiversity dynamics over Earth's history. Despite-or even spurred by-this growing availability of resources, analytical paleobiology faces deep-rooted obstacles that stem from the need for more equitable access to data and best practices to guide analyses of the fossil record. Recent progress has been accelerated by a collective push toward more collaborative, interdisciplinary, and open science, especially by early-career researchers. Here, we survey four challenges facing analytical paleobiology from an early-career perspective: (1) accounting for biases when interpreting the fossil record; (2) integrating fossil and modern biodiversity data; (3) building data science skills; and (4) increasing data accessibility and equity. We discuss recent efforts to address each challenge, highlight persisting barriers, and identify tools that have advanced analytical work. Given the inherent linkages between these challenges, we encourage discourse across disciplines to find common solutions. We also affirm the need for systemic changes that reevaluate how we conduct and share paleobiological research.

Recent advances in availability and synthesis of the economic costs of biological invasions

Biological invasions are a global challenge that has received insufficient attention. Recently available cost syntheses have provided policy- and decision makers with reliable and up-to-date information on the economic impacts of biological invasions, aiming to motivate effective management. The resultant InvaCost database is now publicly and freely accessible and enables rapid extraction of monetary cost information. This has facilitated knowledge sharing, developed a more integrated and multidisciplinary network of researchers, and forged multidisciplinary collaborations among diverse organizations and stakeholders. Over 50 scientific publications so far have used the database and have provided detailed assessments of invasion costs across geographic, taxonomic, and spatiotemporal scales. These studies have provided important information that can guide future policy and legislative decisions on the management of biological invasions while simultaneously attracting public and media attention. We provide an overview of the improved availability, reliability, standardization, and defragmentation of monetary costs; discuss how this has enhanced invasion science as a discipline; and outline directions for future development.

Assembly of functional diversity in an oceanic island flora

Oceanic island floras are well known for their morphological peculiarities and exhibit striking examples of trait evolution1-3. These morphological shifts are commonly attributed to insularity and are thought to be shaped by the biogeographical processes and evolutionary histories of oceanic islands2,4. However, the mechanisms through which biogeography and evolution have shaped the distribution and diversity of plant functional traits remain unclear5. Here we describe the functional trait space of the native flora of an oceanic island (Tenerife, Canary Islands, Spain) using extensive field and laboratory measurements, and relate it to global trade-offs in ecological strategies. We find that the island trait space exhibits a remarkable functional richness but that most plants are concentrated around a functional hotspot dominated by shrubs with a conservative life-history strategy. By dividing the island flora into species groups associated with distinct biogeographical distributions and diversification histories, our results also suggest that colonization via long-distance dispersal and the interplay between inter-island dispersal and archipelago-level speciation processes drive functional divergence and trait space expansion. Contrary to our expectations, speciation via cladogenesis has led to functional convergence, and therefore only contributes marginally to functional diversity by densely packing trait space around shrubs. By combining biogeography, ecology and evolution, our approach opens new avenues for trait-based insights into how dispersal, speciation and persistence shape the assembly of entire native island floras.

Untargeted Metabolomics for Integrative Taxonomy: Metabolomics, DNA Marker-Based Sequencing, and Phenotype Bioimaging

Integrative taxonomy is a fundamental part of biodiversity and combines traditional morphology with additional methods such as DNA sequencing or biochemistry. Here, we aim to establish untargeted metabolomics for use in chemotaxonomy. We used three thallose liverwort species Riccia glauca, R. sorocarpa, and R. warnstorfii (order Marchantiales, Ricciaceae) with Lunularia cruciata (order Marchantiales, Lunulariacea) as an outgroup. Liquid chromatography high-resolution mass-spectrometry (UPLC/ESI-QTOF-MS) with data-dependent acquisition (DDA-MS) were integrated with DNA marker-based sequencing of the trnL-trnF region and high-resolution bioimaging. Our untargeted chemotaxonomy methodology enables us to distinguish taxa based on chemophenetic markers at different levels of complexity: (1) molecules, (2) compound classes, (3) compound superclasses, and (4) molecular descriptors. For the investigated Riccia species, we identified 71 chemophenetic markers at the molecular level, a characteristic composition in 21 compound classes, and 21 molecular descriptors largely indicating electron state, presence of chemical motifs, and hydrogen bonds. Our untargeted approach revealed many chemophenetic markers at different complexity levels that can provide more mechanistic insight into phylogenetic delimitation of species within a clade than genetic-based methods coupled with traditional morphology-based information. However, analytical and bioinformatics analysis methods still need to be better integrated to link the chemophenetic information at multiple scales.

Global models and predictions of plant diversity based on advanced machine learning techniques

Despite the paramount role of plant diversity for ecosystem functioning, biogeochemical cycles, and human welfare, knowledge of its global distribution is still incomplete, hampering basic research and biodiversity conservation. Here, we used machine learning (random forests, extreme gradient boosting, and neural networks) and conventional statistical methods (generalized linear models and generalized additive models) to test environment-related hypotheses of broad-scale vascular plant diversity gradients and to model and predict species richness and phylogenetic richness worldwide. To this end, we used 830 regional plant inventories including c. 300 000 species and predictors of past and present environmental conditions. Machine learning showed a superior performance, explaining up to 80.9% of species richness and 83.3% of phylogenetic richness, illustrating the great potential of such techniques for disentangling complex and interacting associations between the environment and plant diversity. Current climate and environmental heterogeneity emerged as the primary drivers, while past environmental conditions left only small but detectable imprints on plant diversity. Finally, we combined predictions from multiple modeling techniques (ensemble predictions) to reveal global patterns and centers of plant diversity at multiple resolutions down to 7774 km² . Our predictive maps provide accurate estimates of global plant diversity available at grain sizes relevant for conservation and macroecology.

Reference bioimaging to assess the phenotypic trait diversity of bryophytes within the family Scapaniaceae

Macro- and microscopic images of organisms are pivotal in biodiversity research. Despite that bioimages have manifold applications such as assessing the diversity of form and function, FAIR bioimaging data in the context of biodiversity are still very scarce, especially for difficult taxonomic groups such as bryophytes. Here, we present a high-quality reference dataset containing macroscopic and bright-field microscopic images documenting various phenotypic characters of the species belonging to the liverwort family of Scapaniaceae occurring in Europe. To encourage data reuse in biodiversity and adjacent research areas, we annotated the imaging data with machine-actionable metadata using community-accepted semantics. Furthermore, raw imaging data are retained and any contextual image processing like multi-focus image fusion and stitching were documented to foster good scientific practices through source tracking and provenance. The information contained in the raw images are also of particular interest for machine learning and image segmentation used in bioinformatics and computational ecology. We expect that this richly annotated reference dataset will encourage future studies to follow our principles.

Measurement(s)	phenotype
Technology Type(s)	bright-field microscopy
Factor Type(s)	taxonomic identification of different species
Sample Characteristic - Organism	Scapaniaceae

The Limpopo–Mpumalanga–Eswatini Escarpment—Extra-Ordinary Endemic Plant Richness and Extinction Risk in a Summer Rainfall Montane Region of Southern Africa

Climatic, edaphic, and topographic differences between mountains and surrounding lowlands result in mountains acting as terrestrial islands with high levels of endemic biota. Conservation of mountains is thus key to successful biodiversity conservation. The Limpopo–Mpumalanga–Eswatini Escarpment (LMEE) in South Africa and the Kingdom of Eswatini is one of the largest components of southern Africa’s Great Escarpment. Despite botanical collecting effort over 150 years, there has never been a holistic and comprehensive synthesis of plant endemics data for the LMEE. For the first time, we define the LMEE as an orographic entity, covering 53,594 km2; it forms a contiguous highland area from the Pongola River in the south, north to the Woodbush area, and includes rugged western Eswatini. Using exhaustive literature mining, coupled with combined decades of fieldwork by the authors, and up-to-date taxonomic assessments of the 46 undescribed species, we provide the first robust list of plant endemics for the LMEE. The LMEE has 496 endemic plant taxa, comprising 10.7% of the provisional flora (4,657 taxa). This is more than double the endemic plant taxa in the Drakensberg Mountain Centre (DCM), and may be the richest concentration of montane endemics in southern Africa outside of the Core Greater Cape Floristic Region. Grassland hosts the largest number of endemics (74.2%), followed by Savanna (26.6%), then Forest (7.7%). Most endemics of conservation concern occur in Grassland (68.4%), in which one is Extinct and two are Extinct in the Wild. Evolutionary partitioning between Grassland, Savanna and Forest is suggested by low introgression of Biomes at family and genus level, and by a dominance of life-forms adapted to open habitats. High threat statuses for Grassland endemics can be attributed to the historical transformation of almost 20% of Grassland to forestry pre-1990, and ongoing degradation of primary Grassland. With conservation area coverage only 11.1% of the LMEE, the exceptional richness of the endemic flora—combined with major conservation threats—suggest that the LMEE should become a major focus of conservation effort between South Africa and Eswatini as a matter of urgency.

Digitized collections elucidate invasion history and patterns of awn polymorphism in Microstegium vimineum

PREMISE

Digitized collections can help illuminate the mechanisms behind the establishment and spread of invasive plants. These databases provide a record of traits in space and time that allows for investigation of abiotic and biotic factors that influence invasive species.

METHODS

Over 1100 digitized herbarium records were examined to investigate the invasion history and trait variation of Microstegium vimineum. Presence-absence of awns was investigated to quantify geographic patterns of this polymorphic trait, which serves several functions in grasses, including diaspore burial and dispersal to germination sites. Floret traits were further quantified, and genomic analyses of contemporary samples were conducted to investigate the history of M. vimineum's introduction and spread into North America.

RESULTS

Herbarium records revealed similar patterns of awn polymorphism in native and invaded ranges of M. vimineum, with awned forms predominating at higher latitudes and awnless forms at lower latitudes. Herbarium records and genomic data suggested initial introduction and spread of the awnless form in the southeastern United States, followed by a putative secondary invasion and spread of the awned form from eastern Pennsylvania. Awned forms have longer florets, and floret size varies significantly with latitude. There is evidence of a transition zone with short-awned specimens at mid-latitudes. Genomic analyses revealed two distinct clusters corresponding to awnless and awned forms, with evidence of admixture.

CONCLUSIONS

Our results demonstrate the power of herbarium data to elucidate the invasion history of a problematic weed in North America and, together with genomic data, reveal a possible key trait in introduction success: presence or absence of an awn.

Checklist of the mammals (Mammalia) of Colombia

La actualización de la lista de especies presentes en un país es una tarea continua que llena vacíos de información y apoya la toma de decisiones. En los últimos cinco años, ha habido un aumento del número de especies de mamíferos descritas como nuevas en Colombia, así como primeros registros y cambios taxonómicos. Con el fin de actualizar la información de las especies de mamíferos de Colombia, realizamos una revisión exhaustiva de los cambios taxonómicos de las 528 especies registradas en listas previas. Agregamos nuevas especies descritas, así como nuevos registros de especies ya descritas. Discutimos especies cuya presencia ha sido sugerida recientemente en Colombia, pero que no es respaldada por especímenes de museo. La lista actual de mamíferos en Colombia tiene 543 especies, con cuatro descritas en el último año. Esperamos que la lista sea una herramienta apoyar las necesidades de investigación, en especial las extensiones de distribución, los problemas taxonómicos y la conservación de los mamíferos del país. Finalmente, recomendamos que las actualizaciones de la lista sigan estándares nacionales e internacionales como Darwin Core, utilizado por el Repositorio de Información Global sobre Biodiversidad - GBIF, y el Sistema de Información sobre Biodiversidad de Colombia – SiB.

Plant occurrences on the Rybachy and the Sredny Peninsulas, Murmansk Region, Russia: a dataset

Background

The Rybachy and the Sredny Peninsulas are the northernmost part of Murmansk Region in the European part of Russia. While the most part of the Region is covered by boreal forest, the Peninsulas are covered by tundra. The vegetation and flora of Murmansk Region are well studied at present. The Peninsulas were first studied in 1829 by a Finnish botanist Jacob Fellman. The most comprehensive research was conducted in the late 19^th - early 20^th century. Nevertheless, the species composition of the Peninsulas' flora has changed significantly over the past 100 years due to land use and climate change. The aim of this dataset is to make the data on species occurrences for this territory digitally available via GBIF. To date, more or less complete digital floristic data were provided only by the project for digitising the book "Flora of Murmansk Region" (1953–1966).

The present dataset is a part of the project studying the vegetation of the territory. We recorded the information about species frequency and distribution using the relevé method.

New information

We present a dataset based on 991 relevés from all vegetation types, which includes 16,289 records of georeferenced plant occurrences that belong to 568 species. There are 23 species of lichens (Ascomycota), 142 species of mosses (Bryophyta), three species of liverworts (Marchantiophyta) and 400 species of vascular plants (Tracheophyta) in the present dataset. The taxonomic diversity and unevenness result from the vegetation sampling. The data were collected in 2008, 2009, 2011, 2014 and 2015. The dataset cannot be considered as a complete vegetation database or a flora checklist, but it contains the occurrences and frequencies of the species from all the vegetation types.

Open Data Practices among Users of Primary Biodiversity Data

Presence-only biodiversity data are increasingly relied on in biodiversity, ecology, and conservation research, driven by growing digital infrastructures that support open data sharing and reuse. Recent reviews of open biodiversity data have clearly documented the value of data sharing, but the extent to which the biodiversity research community has adopted open data practices remains unclear. We address this question by reviewing applications of presence-only primary biodiversity data, drawn from a variety of sources beyond open databases, in the indexed literature. We characterize how frequently researchers access open data relative to data from other sources, how often they share newly generated or collated data, and trends in metadata documentation and data citation. Our results indicate that biodiversity research commonly relies on presence-only data that are not openly available and neglects to make such data available. Improved data sharing and documentation will increase the value, reusability, and reproducibility of biodiversity research.

A roadmap to plant functional island biogeography

Island biogeography is the study of the spatio-temporal distribution of species, communities, assemblages or ecosystems on islands and other isolated habitats. Island diversity is structured by five classes of process: dispersal, establishment, biotic interactions, extinction and evolution. Classical approaches in island biogeography focused on species richness as the deterministic outcome of these processes. This has proved fruitful, but species traits can potentially offer new biological insights into the processes by which island life assembles and why some species perform better at colonising and persisting on islands. Functional traits refer to morphological and phenological characteristics of an organism or species that can be linked to its ecological strategy and that scale up from individual plants to properties of communities and ecosystems. A baseline hypothesis is for traits and ecological strategies of island species to show similar patterns as a matched mainland environment. However, strong dispersal, environmental and biotic-interaction filters as well as stochasticity associated with insularity modify this baseline. Clades that do colonise often embark on distinct ecological and evolutionary pathways, some because of distinctive evolutionary forces on islands, and some because of the opportunities offered by freedom from competitors or herbivores or the absence of mutualists. Functional traits are expected to be shaped by these processes. Here, we review and discuss the potential for integrating functional traits into island biogeography. While we focus on plants, the general considerations and concepts may be extended to other groups of organisms. We evaluate how functional traits on islands relate to core principles of species dispersal, establishment, extinction, reproduction, biotic interactions, evolution and conservation. We formulate existing knowledge as 33 working hypotheses. Some of these are grounded on firm empirical evidence, others provide opportunities for future research. We organise our hypotheses under five overarching sections. Section A focuses on plant functional traits enabling species dispersal to islands. Section B discusses how traits help to predict species establishment, successional trajectories and natural extinctions on islands. Section C reviews how traits indicate species biotic interactions and reproduction strategies and which traits promote intra-island dispersal. Section D discusses how evolution on islands leads to predictable changes in trait values and which traits are most susceptible to change. Section E debates how functional ecology can be used to study multiple drivers of global change on islands and to formulate effective conservation measures. Islands have a justified reputation as research models. They illuminate the forces operating within mainland communities by showing what happens when those forces are released or changed. We believe that the lens of functional ecology can shed more light on these forces than research approaches that do not consider functional differences among species.

Big Data in Biodiversity Science: A Framework for Engagement

Despite best efforts, the loss of biodiversity has continued at a pace that constitutes a major threat to the efficient functioning of ecosystems. Curbing the loss of biodiversity and assessing its local and global trends requires a vast amount of datasets from a variety of sources. Although the means for generating, aggregating and analyzing big datasets to inform policies are now within the reach of the scientific community, the data-driven nature of a complex multidisciplinary field such as biodiversity science necessitates an overarching framework for engagement. In this review, we propose such a schematic based on the life cycle of data to interrogate the science. The framework considers data generation and collection, storage and curation, access and analysis and, finally, communication as distinct yet interdependent themes for engaging biodiversity science for the purpose of making evidenced-based decisions. We summarize historical developments in each theme, including the challenges and prospects, and offer some recommendations based on best practices.

Comprehensive leaf size traits dataset for seven plant species from digitised herbarium specimen images covering more than two centuries

Background

Morphological leaf traits are frequently used to quantify, understand and predict plant and vegetation functional diversity and ecology, including environmental and climate change responses. Although morphological leaf traits are easy to measure, their coverage for characterising variation within species and across temporal scales is limited. At the same time, there are about 3100 herbaria worldwide, containing approximately 390 million plant specimens dating from the 16th to 21st century, which can potentially be used to extract morphological leaf traits. Globally, plant specimens are rapidly being digitised and images are made openly available via various biodiversity data platforms, such as iDigBio and GBIF. Based on a pilot study to identify the availability and appropriateness of herbarium specimen images for comprehensive trait data extraction, we developed a spatio-temporal dataset on intraspecific trait variability containing 128,036 morphological leaf trait measurements for seven selected species.

New information

After scrutinising the metadata of digitised herbarium specimen images available from iDigBio and GBIF (21.9 million and 31.6 million images for Tracheophyta; accessed date December 2020), we identified approximately 10 million images potentially appropriate for our study. From the 10 million images, we selected seven species (Salixbebbiana Sarg., Alnusincana (L.) Moench, Violacanina L., Salixglauca L., Chenopodiumalbum L., Impatienscapensis Meerb. and Solanumdulcamara L.) , which have a simple leaf shape, are well represented in space and time and have high availability of specimens per species. We downloaded 17,383 images. Out of these, we discarded 5779 images due to quality issues. We used the remaining 11,604 images to measure the area, length, width and perimeter on 32,009 individual leaf blades using the semi-automated tool TraitEx. The resulting dataset contains 128,036 trait records.

We demonstrate its comparability to trait data measured in natural environments following standard protocols by comparing trait values from the TRY database. We conclude that the herbarium specimens provide valuable information on leaf sizes. The dataset created in our study, by extracting leaf traits from the digitised herbarium specimen images of seven selected species, is a promising opportunity to improve ecological knowledge about the adaptation of size-related leaf traits to environmental changes in space and time.

An Ontology-Driven Personalized Faceted Search for Exploring Knowledge Bases of Capsicum

Capsicum is a genus of flowering plants in the Solanaceae family in which the members are well known to have a high economic value. The Capsicum fruits, which are popularly known as peppers or chili, have been widely used by people worldwide. It serves as a spice and raw material for many products such as sauce, food coloring, and medicine. For many years, scientists have studied this plant to optimize its production. A tremendous amount of knowledge has been obtained and shared, as reflected in multiple knowledge-based systems, databases, or information systems. An approach to knowledge-sharing is through the adoption of a common ontology to eliminate knowledge understanding discrepancy. Unfortunately, most of the knowledge-sharing solutions are intended for scientists who are familiar with the subject. On the other hand, there are groups of potential users that could benefit from such systems but have minimal knowledge of the subject. For these non-expert users, finding relevant information from a less familiar knowledge base would be daunting. More than that, users have various degrees of understanding of the available content in the knowledge base. This understanding discrepancy raises a personalization problem. In this paper, we introduce a solution to overcome this challenge. First, we developed an ontology to facilitate knowledge-sharing about Capsicum to non-expert users. Second, we developed a personalized faceted search algorithm that provides multiple structured ways to explore the knowledge base. The algorithm addresses the personalization problem by identifying the degree of understanding about the subject from each user. In this way, non-expert users could explore a knowledge base of Capsicum efficiently. Our solution characterized users into four groups. As a result, our faceted search algorithm defines four types of matching mechanisms, including three ranking mechanisms as the core of our solution. In order to evaluate the proposed method, we measured the predictability degree of produced list of facets. Our findings indicated that the proposed matching mechanisms could tolerate various query types, and a high degree of predictability can be achieved by combining multiple ranking mechanisms. Furthermore, it demonstrates that our approach has a high potential contribution to biodiversity science in general, where many knowledge-based systems have been developed with limited access to users outside of the domain.

Big Data and the United Nations Sustainable Development Goals (UN SDGs) at a Glance

The launch of the United Nations (UN) 17 Sustainable Development Goals (SDGs) in 2015 was a historic event, uniting countries around the world around the shared agenda of sustainable development with a more balanced relationship between human beings and the planet. The SDGs affect or impact almost all aspects of life, as indeed does the technological revolution, empowered by Big Data and their related technologies. It is inevitable that these two significant domains and their integration will play central roles in achieving the 2030 Agenda. This research aims to provide a comprehensive overview of how these domains are currently interacting, by illustrating the impact of Big Data on sustainable development in the context of each of the 17 UN SDGs.

Biodiversity at the global scale: the synthesis continues

Traditionally, the generation and use of biodiversity data and their associated specimen objects have been primarily the purview of individuals and small research groups. While deposition of data and specimens in herbaria and other repositories has long been the norm, throughout most of their history, these resources have been accessible only to a small community of specialists. Through recent concerted efforts, primarily at the level of national and international governmental agencies over the last two decades, the pace of biodiversity data accumulation has accelerated, and a wider array of biodiversity scientists has gained access to this massive accumulation of resources, applying them to an ever-widening compass of research pursuits. We review how these new resources and increasing access to them are affecting the landscape of biodiversity research in plants today, focusing on new applications across evolution, ecology, and other fields that have been enabled specifically by the availability of these data and the global scope that was previously beyond the reach of individual investigators. We give an overview of recent advances organized along three lines: broad-scale analyses of distributional data and spatial information, phylogenetic research circumscribing large clades with comprehensive taxon sampling, and data sets derived from improved accessibility of biodiversity literature. We also review synergies between large data resources and more traditional data collection paradigms, describe shortfalls and how to overcome them, and reflect on the future of plant biodiversity analyses in light of increasing linkages between data types and scientists in our field.

From Reductionism to Reintegration: Solving society's most pressing problems requires building bridges between data types across the life sciences

Decades of reductionist approaches in biology have achieved spectacular progress, but the proliferation of subdisciplines, each with its own technical and social practices regarding data, impedes the growth of the multidisciplinary and interdisciplinary approaches now needed to address pressing societal challenges. Data integration is key to a reintegrated biology able to address global issues such as climate change, biodiversity loss, and sustainable ecosystem management. We identify major challenges to data integration and present a vision for a "Data as a Service"-oriented architecture to promote reuse of data for discovery. The proposed architecture includes standards development, new tools and services, and strategies for career-development and sustainability.

Motivating data contributions via a distinct career currency

If collecting research data is perceived as poorly rewarded compared to data synthesis and analysis, this can slow overall research progress via two effects. People who have already collected data may be slow to make it openly accessible. Also, researchers may reallocate effort from collecting fresh data to synthesizing and analysing data already accessible. Here, we advocate for a second career currency in the form of data contributions statements embedded within applications for jobs, promotions and research grants. This workable step forward would provide for peer opinion to operate across thousands of selection and promotion committees and granting panels. In this way, fair valuation of data contributions relative to publications could emerge.

Connecting high-throughput biodiversity inventories: Opportunities for a site-based genomic framework for global integration and synthesis

High-throughput sequencing (HTS) is increasingly being used for the characterization and monitoring of biodiversity. If applied in a structured way, across broad geographical scales, it offers the potential for a much deeper understanding of global biodiversity through the integration of massive quantities of molecular inventory data generated independently at local, regional and global scales. The universality, reliability and efficiency of HTS data can potentially facilitate the seamless linking of data among species assemblages from different sites, at different hierarchical levels of diversity, for any taxonomic group and regardless of prior taxonomic knowledge. However, collective international efforts are required to optimally exploit the potential of site-based HTS data for global integration and synthesis, efforts that at present are limited to the microbial domain. To contribute to the development of an analogous strategy for the nonmicrobial terrestrial domain, an international symposium entitled "Next Generation Biodiversity Monitoring" was held in November 2019 in Nicosia (Cyprus). The symposium brought together evolutionary geneticists, ecologists and biodiversity scientists involved in diverse regional and global initiatives using HTS as a core tool for biodiversity assessment. In this review, we summarize the consensus that emerged from the 3-day symposium. We converged on the opinion that an effective terrestrial Genomic Observatories network for global biodiversity integration and synthesis should be spatially led and strategically united under the umbrella of the metabarcoding approach. Subsequently, we outline an HTS-based strategy to collectively build an integrative framework for site-based biodiversity data generation.

Data integration enables global biodiversity synthesis

The accessibility of global biodiversity information has surged in the past two decades, notably through widespread funding initiatives for museum specimen digitization and emergence of large-scale public participation in community science. Effective use of these data requires the integration of disconnected datasets, but the scientific impacts of consolidated biodiversity data networks have not yet been quantified. To determine whether data integration enables novel research, we carried out a quantitative text analysis and bibliographic synthesis of >4,000 studies published from 2003 to 2019 that use data mediated by the world's largest biodiversity data network, the Global Biodiversity Information Facility (GBIF). Data available through GBIF increased 12-fold since 2007, a trend matched by global data use with roughly two publications using GBIF-mediated data per day in 2019. Data-use patterns were diverse by authorship, geographic extent, taxonomic group, and dataset type. Despite facilitating global authorship, legacies of colonial science remain. Studies involving species distribution modeling were most prevalent (31% of literature surveyed) but recently shifted in focus from theory to application. Topic prevalence was stable across the 17-y period for some research areas (e.g., macroecology), yet other topics proportionately declined (e.g., taxonomy) or increased (e.g., species interactions, disease). Although centered on biological subfields, GBIF-enabled research extends surprisingly across all major scientific disciplines. Biodiversity data mobilization through global data aggregation has enabled basic and applied research use at temporal, spatial, and taxonomic scales otherwise not possible, launching biodiversity sciences into a new era.

Distribution of birds in Colombia

Background

1. Colombia with 1941 known recorded bird species is one of the most species rich countries in the world. Efforts are necessary to conserve, study and promote sustainable use of this important taxonomic group throughout Colombia’s vast territory.

2. In an ideal world, informed decisions that are based on sound scientific information should be likelier to have successful outcomes. Nevertheless, there are barriers that make it difficult to access and use information in a timely fashion. Those same barriers impede the study, conservation and sustainable use of bird species in Colombia. On the other hand, given that there is good documentation about the ecology of a large number of species, information about the distribution of birds can be easily incorporated into decision-making processes, once this information becomes readily available in a consumable format using Geographic Information Sciences tools.

3. In this context, the main objective of this paper is to present the first compilation of the current distribution of 1889 (97%) species of birds in Colombia, using expert criteria. The shapefiles were used to show the distribution and diversity of bird species in Colombia under both geopolitical and conservation geographic units.

4. The information provided in this paper can be used as a baseline for a huge number of initiatives that aim to strengthen conservation efforts and improve knowledge about one the most unique taxonomic groups in the country. These range from land use planning strategies at the municipal or department scale to sustainable use of bird species - such as those initiatives related to bird watching - in Colombia.

New information

This study has considered three key aspects: 1) the importance of birds for Colombia’s ecosystems, 2) the privileged place of Colombia in bird species richness and 3) the importance of data mobilisation in formats easily consumable by Geographic Information Systems (GIS) to facilitate the processes of informed decision-making. We present the first compilation - in shapefile format - for 1889 of the 1941 bird species recorded from Colombia. Using this novel collection, we showed the species richness of birds in Colombia’s 33 Departments plus its Captial District (DPs), 1122 Municipalities (MNs), 58 protected areas (PAs), 39 Regional Autonomous Corporations (the authorities responsible within their respective jurisdictions for regulating the environment and renewable natural resources in Colombia; CARs) and 916 Collectively Titled Territories (including both indigenous reservations and afro-descendant communities; CTTs). In addition, we provide a list of known bird species richness for the above geographic units found in the available literature. The information provided here can be used as a baseline for a huge number of initiatives concerning the study, conservation and sustainable use of bird species present in Colombia, providing access to key features of bird distribution that should facilitate decision-making.

An inventory of biodiversity data sources for conservation monitoring

Many conservation managers, policy makers, businesses and local communities cannot access the biodiversity data they need for informed decision-making on natural resource management. A handful of databases are used to monitor indicators against global biodiversity goals but there is no openly available consolidated list of global data sets to help managers, especially those in high-biodiversity countries. We therefore conducted an inventory of global databases of potential use in monitoring biodiversity states, pressures and conservation responses at multiple levels. We uncovered 145 global data sources, as well as a selection of global data reports, links to which we will make available on an open-access website. We describe trends in data availability and actions needed to improve data sharing. If the conservation and science community made a greater effort to publicise data sources, and make the data openly and freely available for the people who most need it, we might be able to mainstream biodiversity data into decision-making and help stop biodiversity loss.

Molecular Detection Mapping and Analysis Platform for R (MDMAPR) facilitating the standardization, analysis, visualization, and sharing of qPCR data and metadata

Quantitative polymerase chain reaction (qPCR) has been used as a standard molecular detection tool in many scientific fields. Unfortunately, there is no standard method for managing published qPCR data, and those currently used generally focus on only managing raw fluorescence data. However, associated with qPCR experiments are extensive sample and assay metadata, often under-examined and under-reported. Here, we present the Molecular Detection Mapping and Analysis Platform for R (MDMAPR), an open-source and fully scalable informatics tool for researchers to merge raw qPCR fluorescence data with associated metadata into a standard format, while geospatially visualizing the distribution of the data and relative intensity of the qPCR results. The advance of this approach is in the ability to use MDMAPR to store varied qPCR data. This includes pathogen and environmental qPCR species detection studies ideally suited to geographical visualization. However, it also goes beyond these and can be utilized with other qPCR data including gene expression studies, quantification studies used in identifying health dangers associated with food and water bacteria, and the identification of unknown samples. In addition, MDMAPR’s novel centralized management and geospatial visualization of qPCR data can further enable cross-discipline large-scale qPCR data standardization and accessibility to support research spanning multiple fields of science and qPCR applications.

Awareness and use of biodiversity collections by fish biologists

A survey of 280 fish biologists from a diverse pool of disciplines was conducted in order to assess the use made of biodiversity collections and how collections can better collect, curate and share the data they have. From the responses, data for how fish biologists use collections, what data they find the most useful, what factors influence the decisions to use collections, how they access the data and explore why some fish biologists make the decision to not use biodiversity collections is collated and reported. The results of which could be used to formulate sustainability plans for collections administrators and staff who curate fish biodiversity collections, while also highlighting the diversity of data and uses to researchers.

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

PalmTraits 1.0, a species-level functional trait database of palms worldwide

Plant traits are critical to plant form and function -including growth, survival and reproduction- and therefore shape fundamental aspects of population and ecosystem dynamics as well as ecosystem services. Here, we present a global species-level compilation of key functional traits for palms (Arecaceae), a plant family with keystone importance in tropical and subtropical ecosystems. We derived measurements of essential functional traits for all (>2500) palm species from key sources such as monographs, books, other scientific publications, as well as herbarium collections. This includes traits related to growth form, stems, armature, leaves and fruits. Although many species are still lacking trait information, the standardized and global coverage of the data set will be important for supporting future studies in tropical ecology, rainforest evolution, paleoecology, biogeography, macroecology, macroevolution, global change biology and conservation. Potential uses are comparative eco-evolutionary studies, ecological research on community dynamics, plant-animal interactions and ecosystem functioning, studies on plant-based ecosystem services, as well as conservation science concerned with the loss and restoration of functional diversity in a changing world.